The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency-based time-series analysis, with high-resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda (Ailuropoda melanoleuca). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant panda’s mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24- hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high-resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.

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The Center for Systems Integration and Sustainability at Michigan State University integrates ecology with socioeconomics, demography and other disciplines for ecological sustainability from local, national to global scales.

Coupled Human and Natural Systems(CHANS) are integrated systems in which humans and natural components interact. CHANS research has recently emerged as an exciting and integrative field of cross-disciplinary scientific inquiry to find sustainable solutions that both benefit the environment and enable people to thrive. Visit CHANS-Net, the international network of research on coupled human and natural systems, for information and ways to engage.